There are various career paths in data science, including being a Data Scientist, Machine Learning Engineer, Data Science Consultant, or a Data Science Instructor. Each has its own set of required skills and work style, which you can develop through the right training programs.

Key Insights

  • Data Scientists are tasked with extracting meaning from raw data, developing machine learning algorithms, improving data collection procedures, cleansing and validating data integrity, and building data models.
  • Machine Learning Engineers design and build machine learning systems, run machine learning experiments and tests, and implements machine learning algorithms. They need to understand data modeling and structures, know Python, Java, and R programming, and have strong communication and problem-solving skills.
  • Data Science Consultants are experienced professionals with a deep understanding of data science technologies, tools, and techniques, offering organizations artificial intelligence and machine learning solutions.
  • Data Science Instructors teach data science skills to students and serve as mentors. They must have several years of professional experience and the ability to explain key concepts and lead hands-on activities.
  • Choosing a career path in data science depends on an individual's interest, preferred work style, long-term career goals, and data science training path.
  • Noble Desktop offers both in-person and live online data science classes, including a Python for Data Science Bootcamp and Data Science and Data Analytics Certificate programs. These classes offer hands-on experience, flexible financing options, setup assistance, small class sizes, and real-time guidance from an expert instructor.

Data Scientists work in the field of data science. If you are interested in becoming a Data Scientist, you may wonder about other related career paths. Data Scientists may work closely with other members of a data science team, specialize in specific data science topics, or advance to higher-level positions. This article examines three data science jobs similar to or related to the role of a Data Scientist.

What is a Data Scientist?

Data Scientists extract meaning from raw data to detect patterns and propose solutions that meet an organization’s needs, especially the needs to compete and grow. A Data Scientist’s responsibilities include finding valuable data from data sources, developing machine learning algorithms, improving data collection procedures, cleansing and validating data integrity to ensure accuracy, and detecting patterns and solutions based on data. Data Scientists build models based on data, create data visualizations that communicate patterns and findings to stakeholders, and automate collection processes. Because data plays a critical role in the success of any organization, Data Scientists can build careers in business, technology, finance, nonprofits, and many other industries. 

Those who wish to become a Data Scientist should develop the analytical, statistical, and programming skills needed to manage and interpret raw data. These skills include understanding statistics, machine learning, and reporting tools. Aspiring Data Scientists also benefit from understanding the programming languages R, SQL, Python, Java, and C++. 

Read more about what a Data Scientist does.

Machine Learning Engineer

A Machine Learning Engineer (ML Engineer) designs and builds machine learning systems, runs machine learning experiments and tests, and implements machine learning algorithms. Machine learning is a branch of artificial intelligence focused on using data and algorithms to complete complex tasks similarly to humans. Automating tasks allows organizations to increase productivity and efficiency, gain insights from large data sets, and more. To become a Machine Learning Engineer, you will need to:

Data Science Consultant

A Data Science Consultant might serve as an eternal expert of the data science pertaining to an organization, or a consultant may work freelance for multiple businesses. A Data Science Consultant is an experienced, highly-skilled professional with a thorough understanding of data science technologies, tools, and techniques. Data Science Consultants offer organizations artificial intelligence and machine learning solutions that help to achieve the organization’s objectives. 

Data Science Instructor

A Data Science Instructor teaches data science skills to students so that they can begin a data science career. Data Science Instructors must have several years of professional experience, the ability to explain key concepts and lead hands-on activities, and serve as a mentor to aspiring Data Scientists. Becoming a Data Science Instructor allows those interested in data science and education to pass on critical skills for this growing field.

How to Decide Which Career is Right for You

A key part of determining the right career for you is understanding what you enjoy doing, what areas of data science interest you most, and the kind of work style you prefer. For example, do you prefer to work for an organization or own a freelance business? Do you enjoy working with a team of professionals? Do you like teaching others and have a knack for guiding people through lessons and activities? You will also want to consider:

Learn the Skills to Become a Data Scientist at Noble Desktop

If you are looking to start a new career in data science, you might think the only way for you to become a Data Scientist is by enrolling in a four-year university or pursuing other costly and lengthy educational options. However, there are many alternative methods available to help you transition into a data science career, including data science bootcamps and certificate courses designed to help working professionals gain the skills needed to obtain an entry-level job as a Data Scientist. Exploring in-person and live online data science bootcamps and certificate programs can help you find the class that meets your career goals, budget, and schedule. The first step to finding the class that fits your needs is to understand the differences between in-person classes and live online classes. 

In-person data science classes meet in a traditional classroom setting at a physical location. In-person classes have the advantage of providing all necessary equipment, such as computers and software, and allowing students to network with local professionals such as your classmates and instructor. You also have the advantage of learning from an expert instructor face-to-face. The primary drawback to in-person courses is the extra time and money required to commute to the physical learning location. Live online data science classes offer many of the same benefits as in-person classes, including the ability to learn in real-time from an expert instructor. You can also collaborate with classmates, and you have the advantage of learning remotely. 

Noble Desktop offers several different in-person and live online data science classes that can help you start a career as a Data Scientist. The Python for Data Science Bootcamp teaches students foundational programming concepts and how to handle different data types, use conditional statements to control the flow of a program, use Scikit-Learn, Matplotlib, Numpy, Pandas, and other Python libraries and tools. Noble’s Data Science Certificate program and Data Analytics Certificate program provide a deep dive into the topics and skills essential to launching a career in data science or data analytics and offer one-on-one mentorship and job search assistance. All Noble Desktop classes provide students with hands-on experience, flexible financing options, setup assistance, a free retake, small class sizes, and real-time guidance from an expert instructor.

Learn more about Noble Desktop’s in-person and live online data science classes.

You can also learn more about data science careers and data science learning options with Noble’s free Data Science Learning Hub.